Hi all,

Have a prepared the following work in progress posts to summarizes basic insights from the data we have compiled over the past few months. We have information on migration, weather, land use classifications and recent nightlights (full details shared in data section below). Am currently overlaying rural and urban regions to test our primary hypothesis on the data. Meanwhile sharing maps on regions with high emigration and high temperature increase, to get a spatial sense of data. As a 101 check have compared regions of highest temperature increase with high emigration to sieve any straightforward correspondence.Given the size and complexity of merging these dataset, would be grateful to get your thoughts on any checks/hypotheses/focus regions.

Overview: Net migraiton, long and short term temperature changes

High emigration regions

Further focusing on high emigrating regions, following maps is based on Clicim data, which started from 1975 and ends at 2015, and collates data at a 5 year interval. The map shows the regions where emigration was more than 90%ile globally over the past 40 years, covering around 4k grids globally. The adjoining scale shows compares the highest emigrations within these 4k highest emigrating grids. Based on the maps, we see a consistent churn in China, India, coastal regions of Brazil, Aregntina and parts of equatorial and south Africa, which I believe could be explained to a certain through social mobility and higher growth.

PS:have excluded Tehran from this as it seemed to have some issue with data (recording almost 8million emigration consistently).

High temperature change

Regions with maximum long and short term change in temperature over the past 40 years. Synchronizing with the Clicim timeline, the 2 maps show the highlights the grids with long term increase in temperature from 1900, i.e. taking the difference in annual average temperature from between 1975 & 1900, 2015 & 1900 and 2 maps with short term increase in temp i.e. relative to 1970.

101: Do extreme temperature change correspond with high emigration?

The charts below compare this for short and long term temperature increase.

Data Sources & Assumptions

Data

  • Sources: Migration, Weather, Remote Sensing
  • Handling different resolutions and data merge
    • all the datasets above have been collapsed at Udelaware grid 55km
    • UDelaware grid used as base: size is close to adm2-adm1 boundaries to help integrate census/admin data later
    • All rasters extracted at 55km
    • Clicim raw data aggreagted at 55km

Assumptions

  • Reducing dimensions
    • Weather: choosing months or annual values? (refer to literature)
    • months might display additional variability
    • taking annual for first cut model
    • Weather: which years to consider ?
    • Currenly taking difference from 1900 for all years overlapping with Clcim

Climate Migration: Data Notes

  • Outliers
    • Case of Tehran: 8 million emigrated in 1975